Supplementary Material for: Intermediate versus High Oxygen Saturation Targets in Preterm Infants: A National Cohort Study
Bibliographic record
Abstract
Introduction: Optimal oxygen saturation targets remain unknown for extremely preterm infants. Methods: Cohort analysis of eligible preterm infants born <29 weeks’ gestation admitted between 2011 and 2018 to centers submitting data to the Canadian Neonatal Network (CNN) database. Site questionnaires to determine saturation targets, alarm settings and date of change, allowed assignation of centers to intermediate (88-93%) or high (90-95%) saturation targets. A six-month washout period was applied to sites which switched targets during the study period. Our primary outcome was survival free of major morbidity. Secondary outcomes were death, necrotizing enterocolitis (NEC), bronchopulmonary dysplasia (BPD), treated retinopathy of prematurity (ROP) and evidence of brain injury during admission. Generalized estimating equations were applied to compensate for demographic differences and site practices. Results: There were 2739 infants in the high (mean gestational age (GA) 26 ± 1.6 weeks) and 6813 infants in the intermediate (mean GA 26.2 ± 1.6 weeks) saturation target group. Survival without morbidity was higher in the intermediate target group (adjusted odds ratio (aOR): 1.58; 95% CI 1.04, 2.45). There was no difference in mortality between groups (aOR 0.81; 95% CI: 0.59, 1.11), in NEC, treated retinopathy, or brain injury. On subgroup analysis, restricting data to sites which switched targets during the study, intermediate saturation targets were associated with lower rates of BPD (aOR 0.45; 95% CI 0.28, 0.72). Conclusions: For neonates <29 weeks’ gestation, intermediate saturation target was associated with a higher odds of survival without major morbidity compared to higher oxygen saturation target.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.373 | 0.023 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".